Education
Ph.D., Massachusetts Institute of Technology
Health Sciences and Technology
B.S., Harvard College
Electrical Engineering
Hello! I am a postdoctoral research fellow in machine learning for health in the Computational Health Informatics Program at Boston Children's Hospital working on diabetes technology and digital health.
My postdoctoral research with Dr. Kenneth Mandl focuses on integrating continuous glucose monitoring (CGM) with electronic health record data to improve outcomes in type 1 diabetes. I recently completed my PhD at MIT through the Health Sciences and Technology program advised by Dr. Isaac Kohane. My dissertation focused on machine learning for precision medicine in type 2 diabetes using continuous glucose monitoring. Prior to that, I graduated magna cum laude from Harvard College with an S.B. degree in Electrical Engineering, where I worked on biomedical control for the artificial pancreas.
My research has been supported by the NSF GRFP and the Takeda Fellowship.
Recent News
[March 2026] Our paper on AI for interpreting diabetes data was published in The Lancet Diabetes & Endocrinology.
[December 2025] Presented our work at ML4H 2025.
[November 2025] Our year in review paper was published in NEJM AI.
[October 2025] Gave a talk on the Glycemia Risk Index (GRI) at the Diabetes Technology Meeting. Read the consensus paper here.
[July 2025] Our editorial CGM Analysis 2.0 was published.
[June 2025] Our work on the heterogeneity of CGM features was published.
[April 2025] Started postdoctoral fellowship at Boston Children's Hospital.
[February 2025] Defended my PhD! Read my dissertation here.
[January 2025] Gave an oral presentation at the Pacific Symposium on Biocomputing.
[November 2024] Gave a talk at the Workshop on Machine Learning for Personalized Nutrition and Diabetes Management at IEEE EMBS BHI 2024.
[September 2024] Gave a lightning talk at the NIDDK Workshop on Precision Medicine in Diabetes.
[September 2024] Was selected as a Takeda Fellow to fund the final year of my PhD.
[July 2024] Served as the General Chair for the Women in Machine Learning Symposium at ICML in Vienna.
Research
My research centers on diabetes technology and machine learning for healthcare. Specifically, I am currently working on methods for integrating electronic health record data and wearable data to improve clinical decision making.
Read about my research →Teaching and Mentorship
Teaching and mentoring students is one of the most meaningful parts of my work. I previously served as a Graduate Teaching Development Fellow at MIT, am on the board of Women in Machine Learning, and have served as a Resident Tutor at Harvard College since 2022.
Read about my teaching experience →Academic Service
- Board of Directors, Women in Machine Learning
- Organizing Committee, SAIL
- Proceedings Chair, CHIL
- Organizing Committee, SAIL
- Outreach Chair, ML4H
- Organizing Committee, SAIL
- General Chair, WiML @ ICML
- Workflow Chair, ML4H
- Outreach Sub-Chair, CHIL
- Organizing Committee, SAIL
- Volunteer Team, Responsible AI Symposium
- Planning Team, Path of Professorship (MIT)
Reviewing
- 2026: Nature Health; Scientific Data; IEEE JBHI; JDST; NeurIPS; MLHC; Diabetes, Obesity, and Metabolism
- 2025: Scientific Data; IEEE JBHI; JDST; BMJ Digital Health & AI; NeurIPS; MLHC; CHIL
- 2024: CHIL; AMIA
- 2023: ML4H